Wind Turbine Performance in Controlled Conditions: BEM Modeling and Comparison with Experimental Results
Why this work is in the frame
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Bibliographic record
Abstract
Predictions of the performance of operating wind turbines are challenging for many reasons including the unsteadiness of the wind and uncertainties in blade aerodynamic behaviour. In the current study an extended blade element momentum (BEM) program was developed to compute the rotor power of an existing 4.3 m diameter turbine and compare predictions with reported controlled experimental measurements. Beginning with basic blade geometry and the iterative computation of aerodynamic properties, the method integrated the BEM analysis into the program workflow ensuring that the power production by a blade element agreed with its lift and drag data at the same Reynolds number. The parametric study using the extended BEM algorithm revealed the close association of the power curve behaviour with the aerodynamic characteristics of the blade elements, the discretization of the aerodynamic span, and the dependence on Reynolds number when the blades were stalled. Transition prediction also affected overall performance, albeit to a lesser degree. Finally, to capture blade finite area effects, the tip loss model was adjusted depending on stall conditions. The experimental power curve for the HAWT of the current study was closely matched by the extended BEM simulation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it